BYOD and Productivity Statistics

Last week I started a discussions about BYOD and Productivity because there are lots of people claiming increased productivity from BYOD.

Intuitively I expect this to be correct. Allowing people to work in a way of their choosing, using a device of their choosing, ought to result in better productivity.

Part of the discussion in my previous post was difficulty in defining what productivity was for many job types, but still there ought to be some statistics to support the declaration of ‘increased productivity’ even if it’s only in some example work types? There are, after all, lots of people already doing it.

“Today’s businesses need a smarter, more mobile approach,” said Fergus Murphy, marketing director, client solution, Dell Europe. “If an organisation wishes to remain in a very competitive market, it needs to open its mind and broaden its perspectives.”

The Evolving Workforce Research report found that nearly 60% of employees feel work would be more enjoyable if they had a say in the technologies they used, while 60% feel they would be more productive with better IT resources.

This news article highlights a report from Dell which isn’t directly linked to, but I think it’s referring to this one. This is a report based on a survey of employees. There is reasonably good evidence in these surveys that people feel more productive in a BYOD context, but are they, what is the evidence for it? I’m always a bit sceptical of drawing conclusions from surveys of people’s perceptions. Perceptions are such a poor measure of reality.

One of the things that I do like about this report is the focus on productivity measures moving beyond being simply a function of hours worked. Hours are such a poor measure of productivity if productivity is a measure of the ratio of inputs and outputs.

To help companies determine the current and potential value of BYOD, Cisco IBSG conducted a detailed financial analysis of BYOD in six countries. Our findings show that, on average, BYOD is saving companies money and helping their employees become more productive. But the value companies currently derive from BYOD is dwarfed by the gains that would be possible if they were to implement BYOD more strategically.

This report is also, mainly, based on survey material but it also integrates real world experience. It also creates a classification system for quantifying the benefits:

For different work types (mobile employees moving from corporate devices to BYOD, mobile employees moving from corporate-paid data plans to employee-funded plans, etc.)

And different cost pools (software, support and training, etc.)

As highlighted in a previous post we need to be careful with the term BYOD, especially when it comes to productivity, because it’s not primarily about the device:

It is important to note that productivity improvements come from the device and the software, mobile apps, and cloud services used on these devices. BYOD-ers highly value the ability to use the applications and services of their choice, rather than being limited to what their companies offer.

This statement links to an endnote:

The top overall reason for BYOD, “Can get more done with my own device and applications,” combines the attributes “I can get more done with my own device (it’s faster / better / newer)” and “I can get more done with the software / mobile apps.”

These are the overall statistics:

BYOD-ers save an average of 37 minutes per week with BYOD as it is currently implemented in their companies. The United States leads by far in terms of current productivity gains per BYOD user, with 81 minutes per week, followed by the United Kingdom at 51 minutes. In both of these countries, BYOD-ers posted impressive gains by working more efficiently and being more available to their colleagues and managers.

Most of this benefit comes in the form of improved efficiency.

There are a set of workers surveyed who gain significantly higher productivity benefits of more than 4 hours. The report also has some words of caution on productivity as the other end of the spectrum:

One-quarter of current BYOD-ers would rather have a company-issued device. Moreover, percent of BYOD-ers are very unproductive using their own devices for work. These “problem BYOD-ers” average more than four hours in lost time per week due to using their own devices for work. In India, China, and Brazil, about 20 percent of all BYOD-ers are problem users, twice the rate as in the United States, United Kingdom, and Germany. Because they lose so much time using their own devices for work, problem BYOD-ers in these countries have a negative impact on the overall productivity of BYOD.

The area that this report doesn’t really go into, which I find a disappointment, is the impact upon different work types even though it does state that it believes that the greatest value of BYOD will come from Knowledge Workers. The problem with the term Knowledge Worker is that it is such a broad one.

So some real statistics which are based primarily on surveys and hence perceptions, but interesting all the same.

One more to finish of this time:

I couldn’t leave the subject of BYOD without referring to at least one Infographic, of which the most popular one is, by far one from ReadWrite and Intel – here. This states:

74% of IT leaders believe “BYOD can help our employees be more productive”

and

57 minutes – The average amount of time reclaimed per worker per day in an Intel BYOD program

These two statistics are based on a report by Quest (now Dell) and Intel (pdf).

I’m not going to comment on the Quest (now Dell) report and the 74% figure because I’ve already commented on one Dell report.

By the end of 2011, about 17,000 employees were using personally owned smart phones at Intel and saving an estimated 57 minutes per day – an annual productivity gain for Intel of 1.6 million hours.

Unfortunately there doesn’t seem to be much detail about how Intel came to this figure so it’s not clear whether these benefits were primarily seen by a particular set of work types or whether they encountered any of the concerns raised in the Cisco report.

Also, there’s a bit of a challenge with defining productivity in terms of time gained, because that just leads to the question, time gained to do what?

Like I say, intuitively BYO techniques should lead to improved productivity and there are some interesting productivity statistics to support it, but each one of the has its drawbacks. Why are productivity statistics important though? The reason, personally, that I’m interested is because BYO techniques come with challenges and risks. If you don’t know where the benefits are gained, you don’t know the most appropriate way to overcome the challenges or how to balance the risks. Also, I think it’s important, because if you know where the benefits come from you potentially have the opportunity to innovate beyond where others are already going.

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6 thoughts on “BYOD and Productivity Statistics”

I’ve always been concerned about the decision making quality of a low number of users, out weighing the good decisions of many in BYOD cases, What happens if the ‘own device’ of a “content creator” is an iPad, as opposed to a more fitting business provided device (i.e. full size keyboard, multi display etc), the productivity impact would be devastating. In this argument I’ve often been told that implementations would need “guidelines” But this seems the wrong concept; “Bring your own device, but we’ll tell you what you can have from a list”

Yesterday I would have given my right arm to bring my own device, as my own laptop is more powerful than my business device, but that really it wasn’t the solution, what I actually needed was a business provided tool that could produce the output I needed at the time, who owned that device, well frankly I couldn’t care less :o)

That’s part of the challenge I’ve been grappling with. If you give people a tool then you do so from the perspective that you know that the tool does the job – it may not be the best tool, but it will, it least be functional.

When you let people choose you are allowing the choices to be both good and bad.

Some people’s choice will be surprising, and innovative and produce a new way of working. Other’s will be disastrous.

If you limit the risk of this happening be telling people what fits within a given criteria then you severely limit that ability for people to innovate. You do protect yourself from the person who makes the very bad choice, but at what cost.

What isn’t known is which of these risks is the greater.

Now thankfully, the reducing cost of end user devices means that the impact of a poor choice can normally be rectified with relative ease for a corporation, but that ease might not be as straightforward for the employee who has spent personal money.

You can imagine a situation where an employee uses personal money to enable BYO and makes a poor choice. That poor choice impacts upon their productivity but they don’t have any more personal money to rectify it. So the employer is impacted by the poor choice of the employee.

Likewise, an employee who makes a good choice gives their employer significant productivity advantage, but doesn’t receive any recognition for that improved productivity because it’s not recognisable.